Processor linkages, Farm Productivity and Household Income in Dairy Farm Households in

East AfricaOmondi I.A., Rao E.J.O., Karimov A.A., and Baltenweck, I.

ILRI Institute Planning Meeting4-7 October 2016

Foresight & Policy

Gender & Social Equity

Enhancing Nutrition through Livestock

Value chains for competitive smallholders

systems

Gender equitable control of assets and resources

Improved capacity of women and youth to participate in decision-making

Increased access to diverse nutrient rich foods

Increased livelihood opportunities

Reduced market barriers

Conducive Policy Environment

Our Theory of Change…

* Livestock keepers &

their communities

* Private sector

* Development partners

* Government agencies

* Policy & decision makers

* Research partners

Research teams(Sphere of Control)

Research & near development outcomes(Sphere of Influence)

Sub- IDOs(Sphere of Interest)

Monitoring, Evaluation &

Impact Assessment

Decision making isbased on evidence

Demand for livestock

(products) is adequate

Actors are willing & able to invest in new approaches

Gender transformative

approaches translate into

lasting benefits

Nutrition interventions are win-win

Background

• Why the study? • Linking smallholder farmers to large enterprises:• could be a powerful mechanism to improve access to:

• input and output markets• other productivity-enhancing services

especially for liquidity constrained smallholders

• What we did:• We conducted the study under EADD project• We analysed the effects of household linkages to milk

markets via dairy hubs

Background … contd.

• The dairy hubs: • act as a linkage between the processors and farmers• differ in levels of growth towards sustainability

• Forms of linkages:1. “pure processor” 2. “mixed-linkage”

• Hypothesis:

• Differences in linkages and growth:

• influences revenues, certainty of income, access to inputs

• thus impacting on income and farm performance

• Data from 993 dairy households in Kenya and Uganda

• 36% farmers operated under “pure processor linkage” hubs

• 64% of farmers operated under “mixed linkage” hubs

• Main analyses :• Propensity score matching• Technical efficiency – DEA model

• No significant differences in socioeconomic characteristics

between these two groups

• except herd size in Uganda

Method and Results

• Statistical matching results reveal:

• That participation in hubs leads to higher dairy revenues and total

household income, ceteris paribus

• implying a multiplier effect of dairy revenue

• Higher effects for households participating in “pure processor” hubs

• Data Envelop Analysis results and statistical test reveal1. no strong influence at farm level from processor linkages

2. Hub maturity, linked to PO efficiency,

- does not sufficiently translate to more productive farmers

Results …. contd.

• Linking farmers to large enterprises produces positive

impacts on income

• Yet no evidence of the trickle effect to households’

productivity and input use in dairy

• It is imperative to assess and design linkages that translate

into increased farm productivity

Implications and Conclusions

This work is financed by: EADD project DonorsLivestock and Fish program of the CGIAR

It contributes to the CGIAR Research Program on Livestock and Fish

We also thank all donors who supported ILRI’s research through their contributions to the CGIAR Fund

Acknowledgements

This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.

better lives through livestock

ilri.orgILRI thanks all donors and organizations who globally supported its work through their contributions

to the CGIAR system